Stochastic gradient descent (SGD) is a popular stochastic optimization method in machine learning. Traditional parallel SGD algorithms, e.g., SimuParallel SGD (Zinkevich, 2010), often require all nodes to have the same performance or to consume equal quantities of data. However, these requirements are difficult to satisfy when the parallel SGD algorithms run in a heterogeneous computing environment;

Energy cloud systems continue to shape the future of the energy sector. The complexity of energy cloud systems stems from their widespread and distributed aspects such as renewable energy sources, energy storage, customers engagement, social media and the advancements in communication and computing technologies. The unprecedented large-scale growth of energy cloud systems requires a crucial and dramatic

Page faults occurring within transactions jeopardize concurrency in Intel Restricted Transactional Memory (RTM). To make progress in spite of page-fault-induced aborts, the program must resort to the non-speculative fallback path and re-execute the affected transaction. Since the atomicity of a non-speculative transaction is guaranteed by impeding the execution of any other speculative transactions

Due to their rapid growth and deployment, the Internet of things (IoT) have become a central aspect of our daily lives. Unfortunately, IoT devices tend to have many vulnerabilities which can be exploited by an attacker. Unsupervised techniques, such as anomaly detection, can be used to secure these devices in a plug-and-protect manner. However, anomaly detection models must be trained for a long time

The K-means algorithm is one of the most popular algorithms in Data Science, and it is aimed to discover similarities among the elements belonging to large datasets, partitioning them in K distinct groups called clusters. The main weakness of this technique is that, in real problems, it is often impossible to define the value of K as input data. Furthermore, the large amount of data used for useful

Clustering, which explores the visualization and distribution of data, has recently been studied widely. Although the existing clustering algorithms can well detect arbitrary shape clusters, most of them face the limitation that they cluster points on the basis of two physical metrics, distance and density, but ignore the orientation relationship of data distribution. Beside, they have a difficulty

The technological evolution of the smart grids is going to take its shape in the form of a new paradigm called the Internet of Energy (IoE); which is considered to be the convergence of internet, communication, and energy. Like other evolved technologies, the IoE inherits security vulnerabilities from its constituents that need to be addressed. Intrusion Detection Systems (IDS) have been used to counteract

Smart city projects stand out for including a wide array of communication systems and heterogeneous technologies operated by multiple entities that collect data from citizens in very different ways. Basically, these projects involve three main actors that may have conflicting interests regarding the ownership and exploitation of the generated data: public administrations, service providers and citizens

The blockchain whitepaper contains detailed technical and business information, so its analysis is important for blockchain text mining. Previous works focus on analyze homogeneous objects and relations. The main problem, however, is these works do not take into account the heterogeneity of information. This paper presents a new methodology for whitepapers analysis by designing heterogeneous graph

In this paper, we focus on the design of optimal relay and jammer selection strategy in relay-aided wireless networks. Different from previous works, assuming that the channel state information (CSI) of illegitimate nodes was available and only an eavesdropper existed, we first analyze disadvantages of joint relay and jammer selection (JRJS), average optimal relay selection (AORS), traditional maximum

With the increasing viability of Internet of Things (IoT), more devices are expected to be connected in a smart city environment. It can provide many benefits for people’s daily life, but is also susceptible to many security threats in practice. Intrusion detection systems (IDSs), especially signature-based IDSs, are one of the most commonly adopted security mechanisms to safeguard various network

Reducing the energy expended to carry out a computational task is important. In this work, we explore the prospects of meeting Quality-of-Service requirements of tasks on a multi-core system while adjusting resources to expend a minimum of energy. This paper considers, for the first time, a QoS-driven coordinated resource management algorithm (RMA) that dynamically adjusts the size of the per-core

With the popularity of the Internet of Things (IoT), data integrity verification in the edge cloud storage attracts attentions from many researchers. Due to the over dependence of the Third Party Auditor (TPA) and the dynamical nature of the IoT data, the traditional data integrity verification framework for cloud storage can hardly work. To satisfy the characteristics of the IoT and avoid the over

Herlihy showed that multiprocessors must support advanced atomic objects, such as compare-and-swap, to be able to solve any arbitrary synchronization task among any number of processes (Herlihy, 1991). Elementary objects such as read-write registers and fetch-and-add are fundamentally limited to at most two processes with respect to solving an arbitrary synchronization task. Later, it was also shown

Blockchain has received a widespread attention because of its decentralized, tamper-proof, and transparent nature. Blockchain works over the principle of distributed, secured, and shared ledger, which is used to record, and track data within a decentralized network. This technology has successfully replaced certain systems of economic transactions in organizations and has the potential to overtake

We present a self-stabilizing leader election algorithm for general networks, with space-complexity O(logΔ+loglogn) bits per node in n-node networks with maximum degree Δ. This space complexity is sub-logarithmic in n as long as Δ=no(1). The best space-complexity known so far for general networks was O(logn) bits per node, and algorithms with sub-logarithmic space-complexities were known for the ring

Understanding memory performance in multi-core platforms is a prerequisite to perform optimizations. To this end, this paper presents analytical models based on Stochastic Reward Nets (SRNs) to model and evaluate the memory performance of Non-Uniform Memory Access (NUMA) multi-core architectures. The approach considers the details of the architecture and first proposes a monolithic SRN model that evaluates

The Time-Sensitive Networking (TSN) set of standards introduces in IEEE 802.1 switches and end stations novel features to meet the requirements of a broad spectrum of applications that are characterized by time-sensitive and mission-critical traffic flows. In particular, the IEEE802.1Qbv-2015 amendment introduces enhancements that provide temporal isolation for scheduled traffic, i.e., a traffic class

Parallel computations with irregular memory access patterns are often limited by the memory subsystems of multi-core CPUs, though it can be difficult to pinpoint and quantify performance bottlenecks precisely. We present a method for estimating volumes of data traffic caused by irregular, parallel computations on multi-core CPUs with memory hierarchies containing both private and shared caches. Further

Smart surface is a new conveying technology composed of a 2D planar surface presenting a matrix of distributed autonomous blocks. Every block contains a micro-electro-mechanical system (MEMS) actuator that controls the transfer of a possible object located above the block to the neighboring blocks, using air-jet forces. The spatial characteristics of the blocks impose some limits on the memory, energy

The alternating direction method of multipliers (ADMM) is a powerful operator splitting technique for solving structured convex optimization problems. Due to its relatively low per-iteration computational cost and ability to exploit sparsity in the problem data, it is particularly suitable for large-scale optimization. However, the method may still take prohibitively long to compute solutions to very

Industry 4.0 technological expansion and the multiple accesses to the diverse Smart Grid domains (power networks, control systems, market, customer premises) entail the need to provide efficient interconnection mechanisms with connection from anywhere, at any time and in anyhow. However, this type of requirement should not only consist in imposing interoperability solutions between entities and domains

Identifying long pairwise maximal common substrings among a large set of sequences is a frequently used construct in computational biology, with applications in DNA sequence clustering and assembly. Due to errors made by sequencers, algorithms that can accommodate a small number of differences are of particular interest. Formally, let D be a collection of n sequences of total length N, ϕ be a length

Online Social Networks (OSNs) represent today a big communication channel where users spend a lot of time to share personal data. Unfortunately, the big popularity of OSNs can be compared with their big privacy issues. Indeed, several recent scandals have demonstrated their vulnerability. Decentralized Online Social Networks (DOSNs) have been proposed as an alternative solution to the current centralized

We analyze time and energy performance of distributed computations in heterogeneous systems with hierarchical memory. Different levels of memory hierarchy have different time and energy efficiency. Core memory may be too small to hold whole load to be processed, while computations using external storage are expensive in time and energy. In order to avoid the costs of processing the load in the external

The focus of extracting colossal closed itemsets from high dimensional biological datasets has been great in recent times. A massive set of short and average sized mined itemsets do not confine complete and valuable information for decision making. But, the traditional itemset mining algorithms expend a gigantic measure of time in mining a massive set of short and average sized itemsets. The greater

Edge computing moves the computation closer to the data and the data closer to the user to overcome the high latency communication of cloud computing. Storage at the edge allows data access with high speeds that enable latency-sensitive applications in areas such as autonomous driving and smart grid. However, several distributed services are typically designed for the cloud and building an efficient

Current programming models only provide abstractions for sharing data under a homogeneous consistency model. It is, however, not uncommon for a distributed application to provide strong consistency for one part of the shared data and eventual consistency for another part. Because mixing consistency models is not supported by current programming models, writing such applications is extremely difficult

Three-dimensional Network-on-Chips (3D NoCs) is a popular design choice due to its low packet latency, low network power consumption and high packing density. However, 3D NoCs suffer from high temperature issues. The 3D stacking of Si-layers elongates heat transfer path from different Si-layers to the heat sink resulting in increase in peak temperature of the chip. Since routers of NoCs have high power

This paper addresses the challenges of MPI derived datatype processing and proposes FALCON-X — A Fast and Low-overhead Communication framework for optimized zero-copy intra-node derived datatype communication on emerging CPU/GPU architectures. We quantify various performance bottlenecks such as memory layout translation and copy overheads for highly fragmented MPI datatypes and propose novel pipelining

Latent Sector Errors (LSEs) happen at a significant frequency in the field and can impose a huge risk to data reliability. Disk scrubbing is a background process that reads disks periodically to detect LSEs timely, thus shortening the window of vulnerability to data loss. Nowadays, proactive error prediction, using machine learning techniques, has been proposed to improve storage system reliability

In the recent years, the Smart Grid (SG) system faces various challenges like the ever-increasing energy demand, the enormous growth of renewable energy sources (RES) with distributed energy generation (EG), the extensive Internet of Things (IoT) devices adaptation, the emerging security threats, and the foremost goal of sustaining the SG stability, efficiency and reliability. To cope up these issues

This work presents Speculative Transaction Replication (STR), a protocol that exploits transparent speculation techniques to enhance performance of geo-distributed, partially replicated transactional data stores. In addition, we define a new consistency model, Speculative Snapshot Isolation (SPSI), a variant of Snapshot Isolation (SI), which shelters applications from the subtle anomalies that arise

In recent years, with the rapid development of smart city, prevalent pub/sub (publish/subscribe) streaming systems have been increasingly employed as upstream middleware layer in multi-tenant edge clouds, and feed large volume of data gathered from IoT devices of different tenants into downstream systems (e.g., data analytics and warehouse). A shared tenancy model where multiple untrusted applications

Convolutional neural networks have been proposed as an approach for classifying data corresponding to a variety of datasets. Indeed, developments in data diversity and information technology have increased the complexity of deep learning algorithms. Numerous trained models have been proposed for supporting complex algorithms and data detachment with high accuracy. Convolutional operations increase

Record Linkage (RL) is the task of identifying duplicate entities in a dataset or multiple datasets. In the era of Big Data, this task has gained notorious attention due to the intrinsic quadratic complexity of the problem in relation to the size of the dataset. In practice, this task can be outsourced to a cloud service, and thus, a service customer may be interested in estimating the costs of a record

The current UTXO-based blockchains require the validators to keep the entire ever-growing UTXO set to verify transactions, which is unsuitable for ordinary machines since they occupy a large size of RAM in the long run, resulting in network centralizations. Recently, stateless blockchain technology has been proposed which uses the accumulator to combine the large UTXO set into one short, constant-sized

Finding connected components is one of the most widely used operations on a graph. Optimal serial algorithms for the problem have been known for half a century, and many competing parallel algorithms have been proposed over the last several decades under various different models of parallel computation. This paper presents a class of parallel connected-component algorithms designed using linear-algebraic

The multi-replica strategy can create multiple data replicas for the edge cloud system and store them in different DataNodes, which improves data availability and data service quality. However, the storage resources of DataNodes are limited and the user demand for data is time-varying, the unreasonable number of data replicas will cause a high storage burden on the file system or low data service quality

By increasing mobile devices in technology and human life, using a runtime and mobile services has gotten more complex along with the composition of a large number of atomic services. Different services are provided by mobile cloud components to represent the non-functional properties as Quality of Service (QoS), which is applied by a set of standards. On the other hand, the growth of the energy-source

Software-defined networking (SDN) has evolved as an approach that allows network administrators to program and initialize, control, change and manage networking components (mostly at L2-L3 layers) of the OSI model. SDN is designed to address the programmability shortcomings of traditional networking architectures commonly used in cloud datacenters (CDC). Deployment of SDN solutions have demonstrated

A Cognitive Radio Sensor Network (CRSN) is a distributed network of sensor nodes, which senses event signals and collaboratively communicates over dynamically available spectrum bands in a multi-hop mode. All nodes participating in CRSN have to be cognitive of the network environment and autonomous in decision making for resolving issues related to throughput maximization, delay, and energy minimization

Over the years, switches and network routers have been compromised frequently, and a lot of vulnerabilities have occurred in network infrastructure. Secure routing (SR) is one of the challenges that currently exists in computer networks. Software-defined networks (SDN) are designed by assuming that routers or switches are trustworthy. In SDN, untrusted devices have resulted in security issues such

In recent years, with the continuous expansion of metropolitan area networks, the routing security problem has become more and more serious. In particular, promise-violating attack to inter-domain routing protocol is one of the most difficult attacks to defend, which always leads to serious consequences, such as maliciously attracting traffic and disrupting the network. To deal with such attack, current

We note that a recently described data structure, the Neighborhood Grid, is equivalent to a data structure developed in the mid-1980s called the Monotonic Lagrangian Grid (MLG). The MLG was originally developed to support high-performance molecular and fluid dynamics simulations on both supercomputer and vector processing architectures and still finds use in those and other areas. In this paper we

The paradox between the dramatic development of medical data privacy demand and years of bureaucratic regulation has slowed innovation for electronic medical records (EMRs). We are at a historical point for such innovation to prompt patients data autonomy. In this paper, we propose GuardHealth: an efficient, secure and decentralized Blockchain system for data privacy preserving and sharing. GuardHealth

The smart applications dominating the planet in the present day and age, have innovatively progressed to deploy Internet of Things (IoT) based systems and related infrastructures in all spectrums of life. Since, variety of applications are being developed using this IoT paradigm, there is an immense necessity for storing data, processing them to get meaningful information and render suitable services

With the growth of connectivity to smart grids, new applications, and the changing interaction between customer and energy clouds, clouds are more vulnerable to denial-of-service attacks. Efficient detection methods are required to authenticate, detect and control attackers. Completely Automated Public Turing test to tell Computers and Humans Apart, CAPTCHA, is one efficient tool to thwart denial of

Load balancing, in Cloud Computing (CC) environment, is defined as the method of splitting workloads and computing properties. It enables the enterprises to manage workload demands or application demands by distributing the resources among computers, networks or servers. In this research article, a new load balancing algorithm is proposed as a hybrid of firefly and Improved Multi-Objective Particle

Edge-cloud services provide heterogeneous virtual machine types to run various IoT workloads. Choosing the appropriate VM configuration for each workload can effectively improve performance and reduce costs. This article proposes ARVMEC, Adaptive Recommendation of Virtual Machines for IoT in Edge-Cloud Environment, which can always provide users with the best VM recommendation according to their own

In recent years, large computational problems have beensolved by the distributed environment in which applications are executed in parallel. Also, lately, fog computing or edge computing as a new environment is applied to collect data from the devices and preprocessing is done before sending for main processing in cloud computing. Since one of the crucial issues in such systems is task scheduling,

Along with the rapid growth of the size and complexity of Internet of Things (IoT), the security of terminal devices has increasingly become a focus. In order to ensure the security of terminals, the trusted network connect (TNC) could realize not only the user authentication but also the platform attestation during the network access process. However, the existing TNC infrastructure is based on a

Modern GPGPU supports executing multiple tasks with different run time characteristics and resource utilization. Having an efficient execution and resource management policy has been shown to be a critical performance factor when handling the concurrent execution of tasks with different run time behavior. Previous policies either assign equal resources to disparate tasks or allocate resources based

In this work, we propose Maximal-2-Packing-Halin, a distributed algorithm that finds a maximal 2-packing set in undirected non-geometric Halin graphs of order n in linear time. First, this algorithm finds an external face of the input graph through the application of graph-reduction rules. Second, each vertex determines if it belongs to a maximal 2-packing set by applying a set of vertex-coloring rules

Recently, cloud computing becomes one of the main orientations of many researchers and companies in the IT area. Therefore, a huge number of cloud services have been developed. Because of the diversity and heterogeneity in providing these services, it is urgently needed to develop a unified cloud ontology. Such ontology can classify these services appropriately and participate as a mapping layer to

In prior works, stochastic dual coordinate ascent (SDCA) has been parallelized in a multi-core environment where the cores communicate through shared memory, or in a multi-processor distributed memory environment where the processors communicate through message passing. In this paper, we propose a hybrid SDCA framework for multi-core clusters, the most common high performance computing environment

Wireless Sensor Networks (WSNs) play a significant role in Internet of Things (IoT) to provide cost effective solutions for various IoT applications, e.g., wildlife habitat monitoring, but are often highly resource constrained. Hence, preserving energy (or, battery power) of sensor nodes and maximizing the lifetime of WSNs is extremely important. To maximize the lifetime of WSNs, clustering is commonly

Thus far, Multiview High-Efficiency Video Coding (MV-HEVC) can only use a central processing unit (CPU) to perform decompression on a personal computer (PC) or workstation. Because MV-HEVC is much more complex than High-Efficiency Video Coding (HEVC), decompressors need higher parallelism to decompress in real time. Therefore, this study presents a parallel method based on MV-HEVC. Inter-view complete

In this paper, we consider the problem of decomposing the augmented cube AQn into two spanning, regular, connected and pancyclic subgraphs. We prove that for n≥4 and 2n−1=n1+n2 with n1,n2≥2, AQn can be decomposed into two spanning subgraphs H1 and H2 such that Hi is ni-regular and ni-connected for i=1,2. Moreover, Hi is 4-pancyclic if ni≥3.

Social networks boast a huge number of worldwide users who join, connect, and publish various content, often very large, e.g. videos, images etc. For such very large-scale data storage, data replication using geo-distributed cloud services with virtually unlimited capabilities are suitable to fulfill the users’ expectations, such as low latency when accessing their and their friends’ data. However